| Summary: | 碩士 === 國立暨南國際大學 === 資訊工程學系 === 97 === In the recent years, digital cameras are becoming more and more popular. Many manufacturers of digital cameras have developed a lot of built-in functions to help users taking a high quality picture. However, those built-in functions mainly perform brightness and chroma automatic adjustment and only few of them are about the photographic composition. In fact, a good picture has not only appropriate brightness, contrast and chroma levels, but also a better composition. In this thesis, we combine techniques of face detection and head pose estimation to develop a method for estimating the position and gaze direction of persons in a picture. The proposed method can be used to verify the foreground space position rule. In addition, it can be implemented as a built-in function of a digital camera to detect and to suggest the best view satisfying popular composition rules. In this thesis, we assume that the head pose direction is approximately aligned with the gaze direction. First, we use Viola-Jones’s face detector to detect the face region in a picture. Then, we use the geometric and texture properties of the eyes, nose and mouth to detect the locations of the facial features. Finally, we use the locations of the facial features to determine the head pose from their relative configuration. In 297 test pictures collected from the Internet, the Viola-Jones method achieved a correct face detection rate of 91.9%. When a face is detected, we used the proposed method to determine the face direction and the accuracy of the head pose estimation is 90.7%. The average computation time is about 0.58 second per image.
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